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This article is cited in 4 scientific papers (total in 4 papers)
Information and Computing Technologies in Biology and Medicine
Non-invasive arterial pressure estimating with the cardiac monitor CardioQvark
O. V. Senko, V. Ya. Chuchupal, A. A. Dokukin Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, Moscow, Russia
Abstract:
The outcome of the research on possibility to non-invasively estimate systolic blood pressure is presented. The estimating was performed by applying machine learning techniques to the data acquired with the cardiac monitor CardioQvark. The developed in Russia cardiac monitor represents a portable device capable of registering synchronous electrocardiogram and photoplethysmogram. The presented results confirm the possibility of constructing algorithms capable of estimating systolic blood pressure of individual patients. Also the possibility to construct general purpose algorithms, i.e. algorithms capable of estimating blood pressure of any patient without additional setup, was confirmed.
Key words:
non-invasive estimating, arterial pressure, electrocardiogram, photoplethysmogram, machine learning, cardiac monitor, CardioQvark.
Received 21.11.2017, Published 15.12.2017
Citation:
O. V. Senko, V. Ya. Chuchupal, A. A. Dokukin, “Non-invasive arterial pressure estimating with the cardiac monitor CardioQvark”, Mat. Biolog. Bioinform., 12:2 (2017), 536–545
Linking options:
https://www.mathnet.ru/eng/mbb311 https://www.mathnet.ru/eng/mbb/v12/i2/p536
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